Calculate the number of parameters for a 2D CNN (Convolution Neural Network) layer

default-2023

kernel_width

filter_count

input_channels

kernel_height

bias

Input Channels (D):

The number of parameters in a CNN layer can be calculated using the following equation:((F[0] * F[1] * D) + 1)* K), Kernel Size (F): Size of the convolving kernel (Height, Width)Input Channels (D): The number of channels in the inputadded 1 because of the bias term for each filter. (Optional)Filter Count (K): The number of filters in the convolving layer

Filter Count (K):

Number of parameters for a 2D CNN layer

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